| Autor: |
Beata Toczylowska, Elzbieta Zieminska, Aleksandra Podlecka-Pietowska, Anna Ruszczynska, Malgorzata Chalimoniuk |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Multiple sclerosis and related disorders. 60 |
| ISSN: |
2211-0356 |
| Popis: |
Neuromyelitis optica spectrum disorder (NMOSD) is a disease misdiagnosed with multiple sclerosis (MS). We hypothesized that the serum metabolic profile could be helpful in the differentiation of both diseases in an early stage.We included controls, patients with MS diagnosed according to the McDonald criteria of 2010, and patients with NMOSD diagnosed according to the criteria from 2015. Blood samples were collected on clots from all participants after overnight overfasting. We obtained metabolic profiles using proton magnetic resonance spectroscopy (1HNMR) of serum hydrophilic and hydrophobic compounds. Serum metal levels were measured using isotope-specific detection mass spectrometry (ICP-MS). For statistical analyzes, we used ANOVA tests and multivariate analysis (MVA) - orthogonal partial least square discriminant analysis (OPLS-DA).We analyzed metabolite levels in patient groups compared to controls. We observed significantly different levels of ten metabolite signals in patients with MS vs controls and eighteen metabolite signals in patients with NMSOD vs controls. We observed significantly different levels of five signals in patients with MS vs NMOSD. In the MVA analysis of patient groups, we indicated compounds that most differentiated the groups. All of these compounds are involved in cycles connected to the inflammation process and/or oxidative stress. The results of metallomics studies confirmed metal participation in these processes.It is possible to distinguish patients with MS and NMOSD from controls using ANOVA and MVA tests. The chosen metabolite profile analyzes might possibly be helpful in distinguishing the two diseases from each other in some seronegative and radiologically negative cases. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect